# Systematic Identification of Molecular Signatures Dictating Therapeutic Effects of Clinically First‐Line Chemotherapy Regimens for Human Gastric Cancer Patients Based on Organoid Model

## TL;DR

This study uses organoid models to identify molecular signatures that predict how gastric cancer patients respond to first-line chemotherapy treatments.

## Contribution

The study introduces a system combining organoid screening and transcriptome analysis to identify molecular signatures of chemotherapy response in gastric cancer.

## Key findings

- PDOs responding well to chemotherapy showed high P53 pathway gene expression and low cell proliferation gene expression.
- A chemotherapy-based tumor classification for gastric cancer was established and validated using TCGA and public drug response datasets.
- Organoid models were used to systematically evaluate five first-line chemotherapy regimens for gastric cancer.

## Abstract

Chemotherapy is the mainstay in the treatment of advanced gastric cancer (GC); yet, GC showed diverse responses to first‐line chemotherapy regimens and the underlying molecular basis is still not clear. Here, we established a system that combined organoid‐based chemotherapy regimen screening and transcriptome‐based evaluation to identify underlying molecular signatures of different responses to chemotherapy. We generated 19 GC patient‐derived organoids (PDOs) from surgically resected specimens with corresponding histological characteristics of parent tumors and tested all of the five most commonly used first‐line chemotherapy regimens. Based on the treatment responses, PDOs were classified into double‐sensitive, single‐sensitive, and not‐sensitive groups. PDOs that responded well to chemotherapy presented high expression levels of the P53 pathway genes and low expression levels of cell proliferative activity genes. Furthermore, the chemotherapy‐based tumor classification of GC was established. The GC tumor classification was verified by multi‐omics features from the TCGA dataset and public drug response datasets. In conclusion, this study systematically evaluated clinical chemotherapy regimens for GC and identified chemotherapy response‐associated molecular signatures based on human GC organoids, which are beneficial to the precise treatments of GC.

Chemotherapy is the mainstay in the treatment of advanced gastric cancer (GC); yet, GC showed diverse responses to first‐line chemotherapy regimens and the underlying molecular basis is still not clear. Here, we established a system that combined organoid‐based chemotherapy regimen screening and transcriptome‐based evaluation to identify underlying molecular signatures of different responses to chemotherapy. We generated 19 GC patient‐derived organoids (PDOs) from surgically resected specimens with corresponding histological characteristics of parent tumors and tested all of the five most commonly used first‐line chemotherapy regimens. Based on the treatment responses, PDOs were classified into double‐sensitive, single‐sensitive, and not‐sensitive groups. PDOs that responded well to chemotherapy presented high expression levels of the P53 pathway genes and low expression levels of cell proliferative activity genes. Furthermore, the chemotherapy‐based tumor classification of GC was established. The GC tumor classification was verified by multi‐omics features from the TCGA dataset and public drug response datasets. In conclusion, this study systematically evaluated clinical chemotherapy regimens for GC and identified chemotherapy response‐associated molecular signatures based on human GC organoids, which are beneficial to the precise treatments of GC
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